The KITTI 3D object detection benchmark [1]} is divided into 7,481 training samples and 7,518 testing samples. The training samples are commonly divided into a train set (3,712 samples) and a
val set (3,769 samples) following [2]}, which is also adopted here. We compare CaDDN with existing methods on the test set by training our model on both the train and val sets. We evaluate on the val set for ablation by training our model on only the train set.
